Vehicular navigation based on site specific sensor quality data

ABSTRACT

A method and system for determining a location of a vehicle, the method comprises determining reception location data within a first cell of a work area for a vehicle. A reception quality estimator estimates reception quality data for the corresponding reception location data for the first cell. Optical location data is determined within a first cell of a work area for a vehicle. An optical quality estimator estimates optical quality data for the corresponding optical location data for the first cell. A data processor selects at least one of the reception location data and the optical location data as refined location data associated with the first cell based on the estimated reception quality data and estimated optical quality data.

This document claims priority based on U.S. provisional application Ser.No. 60/655,544, filed Feb. 23, 2005, and entitled VEHICULAR NAVIGATIONBASED ON SITE SPECIFIC SENSOR QUALITY DATA under 35 U.S.C. 119(e).

FIELD OF THE INVENTION

This invention relates to vehicular navigation based on site specificsensor quality data.

BACKGROUND OF THE INVENTION

Location sensing devices include odometers, Global Positioning Systems(GPS), and vision-based triangulation systems, for example. Manylocation sensing devices are subject to errors (e.g., measurement error)in providing an accurate location estimate over time and differentgeographic positions. The error in the location estimate may vary withthe type of location sensing device. Odometers are subject to materialerrors from slipping or sliding over a surface terrain. For example,wheel or tire slippage may cause the odometer to estimate an erroneouslocation for a corresponding vehicle. A Global Positioning System (GPS)may suffer from errors or lack of availability because one or moresatellite transmissions are attenuated or reflected by buildings, trees,hills, terrain or other obstructions. Vision based triangulation systemsmay experience error over certain angular ranges and distance rangesbecause of the relative position of cameras and landmarks. Thus, thereis a need to improve the accuracy and the availability of locationsensing devices for a vehicle to facilitate accurate navigation of thevehicle within a work area.

SUMMARY OF THE INVENTION

In accordance with one embodiment, a method and system for determining alocation of a vehicle, reception location data is determined within afirst cell of a work area for a vehicle. A reception quality estimatorestimates reception quality data for the corresponding receptionlocation data for the first cell. Optical location data is determinedwithin a first cell of a work area for a vehicle. An optical qualityestimator estimates optical quality data for the corresponding opticallocation data for the first cell. A data processor selects at least oneof the reception location data, the optical location data, and otherlocation data as refined location data associated with the first cellbased on the estimated reception quality data and estimated opticalquality data.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a system for determining a location of avehicle based on site specific sensor quality data.

FIG. 2 is a flow chart of a first method for determining a location of avehicle based site specific sensor quality data.

FIG. 3 is a flow chart of a second method for determining a location ofa vehicle.

FIG. 4 is a flow chart of a third method for determining a location of avehicle.

FIG. 5 is a flow chart of a fourth method for determining a location ofa vehicle.

FIG. 6 is a flow chart of a method for navigation of a vehicle inaccordance with a sensor hierarchy.

FIG. 7 is a map of error magnitude contours of one or more locationsensing devices in a work area.

FIG. 8 is a map of navigation modes associated with particularcorresponding zones of the work area of FIG. 7.

FIG. 9 is a map of an illustrative vehicular path that traversesnavigation modes of the work area.

FIG. 10 is a flow chart of another method for determining a location ofa vehicle.

FIG. 11 is a flow chart of yet another method for determining a locationof a vehicle.

DESCRIPTION OF THE PREFERRED EMBODIMENT

In accordance with one embodiment, FIG. 1 shows a system 11 fordetermining a location of a vehicle based on site specific sensorquality data. The system 11 comprises a location-sensing system 10coupled to a vehicular controller 44. A path planning module 42 mayprovide a path plan or other navigation-related input data to thevehicular controller 44. The obstacle detection system 52 may providenavigation-related input on stationary or moving objects within a workarea (e.g., to avoid collisions with such objects). In turn, thevehicular controller 44 may communicate with (e.g., issue control dataor signals to) one or more of the following: a steering system 46, abraking system 48, and a propulsion system 50.

In one embodiment, the location sensing system 10 comprises alocation-determining receiver 12, an optical location determining system14, and a dead-reckoning system 16 that are coupled to a qualityestimation module 20. The location determining receiver 12, the opticallocation determining system 14, and the dead-reckoning system 16 may becollectively referred to as location sensors. Any of the locationsensors may be referred to individually as a location sensor.

The location determining receiver 12 may comprise a Global PositioningSystem (GPS) receiver with differential correction, or another receiverfor receiving electromagnetic energy from transmitters (e.g.,terrestrial or satellite beacons) to determine a location (e.g., in twodimensional or three dimensional coordinates) of the vehicle. Thelocation-determining receiver 12 (e.g., GPS receiver) communicates to areception quality estimator 22; the optical location-determiningreceiver 12 (e.g., vision-based triangulation system) communicates to anoptical quality estimator 23; and the dead-reckoning system 16 (e.g.,differential odometer) communicates with a dead-reckoning qualityestimator 24. The location-determining receiver 12 outputs receptionlocation data 26. Reception location data may also be referred to asprimary location data, whereas all other location data from locationsensors (e.g., of the location-sensing system 10) may be referred to assecondary location data (e.g., optical location data, odometer locationdata, radio frequency ranging location data, gyro location data,magnetometer location data, and accelerometer location data).

The optical location-determining system 14 outputs optical location data28. The optical location-determining system 14 may comprise a lasersystem, a scanning laser system, a ladar (e.g. laser radar) system, alaser range finder, a stereo vision system, a monocular vision system, amachine vision system, or the like. The optical location-determiningsystem may operate over the humanly visible light spectrum, infra-red,near-infra-red or ultraviolet light spectrum, for example.

In an alternate embodiment, the optical location-determining system 14may be replaced by a terrestrial or local radio frequency (RF) rangingsystem that estimates the location of a vehicle by measuring the time ofarrival, the angle of arrival or both of a radio frequency signaltransmitted from one or more fixed or known locations within a maximumradius of the work area. Accordingly, if the optical locationdetermining system 14 is replaced by a local radio frequency rangingsystem, the optical location data is replaced with radio frequency (RF)location data.

In general, the dead-reckoning system 16 comprises a displacement sensorand a heading sensor. The displacement sensor measures the relativedisplacement of the vehicle, whereas the heading sensor measures therelative heading. The dead-reckoning system 16 outputs dead-reckoninglocation data 30. The dead-reckoning location data may provide atraveled distance of the vehicle, a traveled direction of the vehicle,traveled distance versus time (e.g., vehicular speed), or vehicularvelocity (e.g., speed and heading).

In one embodiment, the dead-reckoning system 16 comprises an odometer asthe displacement sensor and a gyroscope (e.g., a fiberoptic gyroscope)as the heading sensor. The odometer may directly or indirectly countwheel revolutions or fractions thereof, of one or more wheels associatedwith the vehicle. The gyroscope may provide vehicle directioninformation or heading information.

In alternate embodiments the dead-reckoning system 16 may comprise oneor more of the following: a wheel revolution counter, an integratorassociated with a speed sensor, an integrator associated with a radarsystem, a gyro, a fiberoptic gyroscope, a vibration gyroscope, amagnetometer, and an accelerometer. The output of an accelerometer maybe double-integrated to determine displacement, for example.

The optical location-determining system 14 may comprise a plurality ofcameras mounted around a perimeter of the work area or inside the workarea to determine vehicle location from stereo vision information, forexample. If the cameras are mounted on or near a perimeter of the workarea, rather than on the vehicle itself, the opticallocation-determining system 14 may be considered an “outside-looking-in”system.

The dead-reckoning location data 30 may comprise a covered distance anda corresponding heading of the vehicle. In one embodiment, thedead-reckoning system 16 may use an optical or magnetic source coupledto a rotational member (e.g., a wheel, or shaft in the drive train) thatemits an optical signal or magnetic field, which is sensed by a sensorto determine the amount of revolutions or fractional revolutions of awheel of the vehicle. The revolutions of the wheel may be converted intoestimated distance. In other embodiments, an odometer or other componentof the dead-reckoning system may be mechanically coupled to a rotationalmember of a drive train or a wheel. Because the dead-reckoning error(e.g., approximately equal to ten (10) percent) of the dead-reckoningsystem 16 may be greater than that of radar system (e.g., typical errorless than three percent) or a location-determining receiver, thedead-reckoning system 16 may be supplemented with readings from a radarsystem, a location-determining receiver, and an accelerometer toestimate velocity of the vehicle, position of the vehicle, or both.

The quality estimation module 20 outputs one or more of the followingquality data to a data processor 38: reception quality data 32, opticalquality data 34, and dead-reckoning quality data 36. The receptionquality data 32 may vary with the vehicle location of the vehicle in thework area. The optical quality data 34 may vary with the vehiclelocation of the vehicle in the work area. The dead-reckoning qualitydata 36 (e.g., odometer quality data and gyroscope quality data) mayvary with the vehicle location of the vehicle in the work area. Thereception quality estimator 22 estimates or determines reception qualitydata 32 (e.g., Dilution of Precision (DOP) data); the optical qualityestimator 23 estimates or determines optical quality data 34 (e.g.,Dilution of Precision or a figure of merit for the reported positionbased on at least one of technical specifications of a vision sensor ofthe optical location determining system 14, an observed scene for thefirst cell, and an imaging processing algorithm for the optical locationdata.); and the odometer quality estimator 24 estimates or determinesdead-reckoning quality data 36.

To create site specific error data for each location sensor, thelocation sensors may take a number of samples of reception location data26, optical location data 28, and dead-reckoning location data 30 forknown or verifiable locations within the work area (e.g., within allcells of a work area and for each location sensor). Error levels,availability, or reliability levels (e.g. in percentage terms) may bedetermined for respective coordinates within the work area by comparingthe measured location of each location sensor to the known or verifiablelocation. The error level data, availability data or reliability datamay be expressed as quality data. For example, the reception qualitydata 32 may comprise Dilution of Precision (DOP). The quality estimationmodule 20 may facilitate the storage of site-specific error data foreach location sensor (e.g., location determining receiver 12, opticallocation-determining system 14, and dead-reckoning system 16) for thevehicle in the data storage device 39.

Dilution of Precision (DOP) is an indicator of the quality of a positiondata (e.g., GPS position data) which considers the relative locations ofsatellites and their geometric relationship to the location determiningreceiver. For example the DOP may consider the number of satellites thatare available (e.g., capable of being received with a reliable signalstrength, a signal quality level, a maximum bit or symbol error rate) toa location determining receiver from particular geographic coordinatesof the location determining receiver at a given time. In accordance withone embodiment, a low DOP value indicates a higher probability ofaccuracy. A DOP may comprise any of the following: Position Dilution ofPrecision, Relative Dilution of Precision, Horizontal Dilution ofPrecision, Vertical Dilution of Precision, Time Dilution of Precision,and Geometric Dilution of Precision. Position Dilution of Precisionrefers to a DOP value for the particular three dimensional location orcoordinates of the location determining receiver, which is a unit-lessfigure of merit expressing the relationship between error in thelocation determining receiver position and error in satellite position.Relative Dilution of Precision provides an indication of the adequacy ofobservations of a location determining receiver during real-timesurveying of measurements. Horizontal Dilution of Precision refers toDOP with respect to latitude and longitude measurements. Verticaldilution of precision refers to DOP with respect to height. TimeDilution of Precision refers to DOP with respect to variations overtime.

A user interface 18 may comprise a keyboard, keypad, a display, apointing device (e.g., mouse, trackball), a magnetic disc drive, amagnetic tape drive, an optical disc, a data port (e.g., parallel,serial or a Universal Serial Bus (USB) port), or another mechanism forinputting or entering input data. A user interface 18 may support theinput or entry of data that is used to assess the quality of thereception location data 26, the optical location data 28, and thedead-reckoning location data 30. A user interface 18 may support theentry of true or precision coordinates, location, or bearing of thevehicle from ancillary equipment, such as survey equipment, opticalsurveying equipment, laser surveying equipment, or otherwise tocalibrate, ground-reference or estimate error level (and to facilitaterespective quality data estimates) for the output of thelocation-determining receiver 12, the optical location-determiningsystem 14, and the dead-reckoning system 16.

The data processor 38 may receive or obtain reception location data 26from the location-determining receiver 12, optical location data 28 fromthe optical location-determining system 14, and dead-reckoning locationdata 30 from the dead-reckoning system 16. The reception location data26 is associated with corresponding reception quality data 32; theoptical location data 28 is associated with corresponding opticalquality data 34; and the dead-reckoning location data 30 is associatedwith corresponding dead-reckoning quality data 36. The data processor 38may be used to implement or control a switching matrix, or a filter suchthat an output comprises refined location data 40.

In a first example, the data processor 38 selects a preferential one ofthe reception location data 26, optical location data 28, anddead-reckoning location data 30 for corresponding distinct locations orzones within the work area. For example, the work area may be dividedinto a first set of zones where reception location data 26 is used toguide the vehicle or plan a path plan for the vehicle; a second set ofzones where the optical location data 28 is used to guide the vehicle orplan a path plan for the vehicle; and a third set of zones where thedead-reckoning location data 30 is used to guide the vehicle or plan apath plan for the vehicle. The refined location data 40 may representselection of the most reliable or accurate data for a corresponding zonewhen a vehicle is in such a zone.

In a second example, the data processor 38 selects a preferential one ofthe reception location data 26, optical location data 28, anddead-reckoning location data 30 for corresponding distinct locations orcells within the work area. For example, the work area may be dividedinto a first set of cells where reception location data 26 is used toguide the vehicle or plan a path plan for the vehicle; a second set ofcells where the optical location data 28 is used to guide the vehicle orplan a path plan for the vehicle; and a third set of cells where thedead-reckoning location data 30 is used to guide the vehicle or plan apath plan for the vehicle. The refined location data 40 may representselection of the most reliable or accurate data for a corresponding zonewhen a vehicle is in such a zone. The member of the first set of cellsmay be contiguous or noncontiguous. The member of the second set ofcells may be contiguous or noncontiguous. The member of third set ofcells may be contiguous or noncontiguous.

In a third example, the data processor 38 may facilitate the applicationof a first weight to reception location data 26 based on the receptionquality data 32 for a particular vehicle location, a second weight tooptical location data 28 based on the optical quality data 34 for aparticular vehicle location, and a third weight to dead-reckoninglocation data 30 based on the dead-reckoning quality data 36.Accordingly, a priori site-specific localization sensor information canbe used to weight or select individual location sensors (alone or incombination) to be used for a position fix or determination of thevehicle.

The data processor 38 is coupled to a data storage device 39 for storinga prior site specific location sensor data, refined location data,cellular definition data (e.g., for a first cell), zone definition data(e.g., for a first zone, a second zone, and third zone), receptionquality data versus cellular location, reception quality data versuszone data, optical quality data versus cellular location, opticalquality data versus zone data, dead-reckoning quality data 36 versuscellular location, and dead-reckoning quality data 36 versus zone data,preferential location data type (e.g., reception location data, opticallocation data, and odometer location data) versus cellular location,preferential location data type versus zone, and cellular locationsversus a first indicator of reception location data (as preferentiallocation data or refined location data for a cell), and cellularlocations versus a second indicator of optical location data (aspreferential location data or refined location data for a cell). Thefirst indicator (e.g., number or symbol) is distinct from the secondindicator. The data storage device 39 may store any of the foregoingdata as a matrix, a look-up table, a database, a relational database,tabular data entries, a file or as another data structure. Further, thematrix may comprise a multi-dimensional matrix that varies with time,because the reliability of the reception location data or other locationdata may vary with time (e.g., as different constellations and numbersof satellites are available at a particular geographic coordinates.) Thedata storage device 39 may comprise memory, a register, an optical diskdrive, a magnetic disk drive, a magnetic storage device, an opticalstorage device, or the like.

The vehicle controller may generate control signals for the steeringsystem 46, a braking system 48 (if present), and a propulsion system 50that are consistent with tracking a path plan, provided by the pathplanning module 42. For example, the control signals may comprise asteering control signal or data message that is time dependent anddefines a steering angle of the steering shaft; a braking control signalor data message that defines the amount of deceleration, hydraulicpressure, or braking friction applied to brakes; a propulsion controlsignal or data message that controls a throttle setting, a fuel flow, afuel injection system, vehicular speed or vehicular acceleration. If thevehicle is propelled by an electric drive or motor, the propulsioncontrol signal or data message may control electrical energy, electricalcurrent, or electrical voltage to the electric drive or motor.

The steering system 46 may comprise an electrically controlled hydraulicsteering system 46, an electrically driven rack-and-pinion steering, anAckerman steering system 46, or another steering system 46. The brakingsystem 48 may comprise an electrically controlled hydraulic brakingsystem 48, or another electrically controlled friction braking system48. The propulsion system 50 may comprise an internal combustion engine,an internal combustion engine electric hybrid system, an electric drivesystem, or the like.

The path planner 42 may use a priori information to limit the maximumerrors from the location-sensing system 10 that might otherwiseaccumulate. Error from the dead-reckoning system 16 and/or a gyroscopemight tend to accumulate without reference data fro application to anerror detection and correction algorithm. The path planner 42 may alsouse maximum calculated errors to adjust overlap from pass to pass orwithin a pass. The path planner 42 may use camera pan, tilt, zoom ratelimits of a an optical location-determining system 14 to construct pathsto avoid the vehicle exceeding those limits.

FIG. 2 discloses a method for determining a location of a vehicle basedon site specific sensor quality data. The method of FIG. 2 begins instep S200.

In step S200, a location-sensing system 10 or location-determiningreceiver 12 determines reception location data 26 within a first cell ofa work area for a vehicle. The work area may be divided into a number ofcells. The first cell is any cell within the work area where the vehicleis located. The cell may be defined by its boundaries or its centerpoint, for example. Although the exact coordinates of the vehicle maynot be known because of potential error in the location sensors, underone illustrative technique for executing step S200, the size of thefirst cell may be selected to be sufficient to contain the vehicle withallowance for the potential error at least for a certain reliabilitylevel.

In step S202, a quality estimation module 20 or reception qualityestimator 22 estimates reception quality data for the correspondingreception location data 26 for the first cell. The work area may bedivided into a group of cells or coordinate ranges, where each cell orcoordinate range is associated with a respective reliability,availability and/or error of localization of the location determiningreceiver 12 or the reception location data 26. Where the work area isdivided into such cells or coordinate ranges, the quality estimator 20or reception quality estimator 22 may retrieve or access receptionquality data 32 for a corresponding first cell.

In one embodiment, the estimated reception data 32 of step S202 is basedon satellite position forecasts for the work site for the particulartime of operation of the vehicle in the work area. For example, thereception quality data may be related to the relative orbital positionsor spatial coordinates of the satellites used in the position solution.Further, the greater the number of satellites that can be used in thesolution or that are available for reception by the location determiningreceiver a particular geographic coordinates at a particular time, themore accurate the solution will generally be. A satellite is availablefor reception if the location determining receiver at particulargeographic coordinates at a particular time can receive and decode thesatellite's transmission with sufficient reliability, which may dependupon received signal strength, received signal quality, received biterror rate, received symbol error rate, demodulation techniques,decoding techniques for the pseudo-random noise code, or other technicalconstraints. Obstructions (e.g., stadium walls and protective roofs) mayimpact the number of satellites used in a solution or the reliability ofthe one or more received satellite signals. The reception quality datamay be expressed as a dilution of precision (DOP), or a subclass orvariant thereof. The dilution of precision can be calculated by locationwithin the worksite (e.g., by using satellite position forecasts for thetime the stadium will be mowed) or measured empirically with alocation-determining receiver 12 (e.g., GPS receiver) that reports DOPrecorded at various positions within the work area or site over a periodof time.

In step S204, an optical location-determining system 14 determinesoptical location data 28 within a first cell of a work area for avehicle.

In step S206, a quality estimation module 20 or an optical qualityestimator 23 estimates optical quality data for the correspondingoptical location data 28 for the first cell. The work area may bedivided into a group of cells or coordinate ranges, where each cell orcoordinate range is associated with an availability and or error oflocalization of the optical location-determining system 14 or theoptical location data 28. Where the work area is divided into such cellsor coordinate ranges, the quality estimating module 20 may retrieve oraccess optical quality data 34 for a corresponding first cell.

If the optical location determining system 14 comprises a vision-basedtriangulation system that comprises cameras (e.g., stationary cameras)mounted around a perimeter of a work area, the optical quality data maybe calculated based on camera parameters (e.g., lens parameters,luminance sensitivity) and locations of the vehicle in the work area.Under one embodiment, the optical quality estimate is based on cameraparameters and corresponding locations (e.g., in two or threedimensional coordinates) of one or more cameras associated with the workarea.

In step S208, a data processor 38 selects at least one of the receptionlocation data 26, the optical location data 28, or other data as refinedlocation data 40 associated with the first cell based on the estimatedreception quality data and the estimated optical quality data. Theselection process of step S208 may be executed in accordance withvarious techniques, which may be applied separately or cumulatively.Under a first technique, the data processor 38, filter or switchingmatrix establishes relative weights for application of the receptionlocation data 26 and the optical location data 28 based on the estimatedreception quality data 32 and estimated optical quality data 34. Underthe second technique, the data processor 38, filter or switching matrixselects comprises organizing the work area into a first zone where thereception location data 26 is selected exclusively as the refinedlocation data 40. Under a third technique, the data processor 38, filteror switching matrix organizes the work area into a second zone where theoptical location data 28 is selected exclusively as the refined locationdata 40. Under a fourth technique, the data processor 38, filter, orswitching matrix organizes the work area into a third zone where boththe reception location data 26 and the optical location data 28 isselected as the refined location data 40.

Under a fifth technique, the data processor 38, filter or switchingmatrix assigns each cell in the matrix one of a group of possible modes.Under a first mode, reception location data 26 is applied as the refinedlocation data 40. Under a second mode, optical location data 28 isapplied exclusively as the refined location data 40. Under a third mode,the dead-reckoning location data 30 is applied exclusively as therefined location data 40. Under a fourth mode, a combination of at leasttwo of the reception location data 26, the optical location data 28, andthe dead-reckoning location data 30 is applied as the refined locationdata 40.

Under a sixth technique, the data processor 38 may select other locationdata (e.g., odometer location data) where the reception quality data 32falls below a first threshold and where the optical quality data 34falls below a second threshold.

During or after step S208, the data processor 38 may define first cellwith reference to the refined location data and store the first celllocation, center point or boundaries in data storage device 39 alongwith the corresponding selection of refined location data for subsequentreference. Accordingly, if the vehicle traverses the first cell again,the data processor 38 may retrieve (from the data storage device 39)whether the optical location data, and the reception location data (orweighted optical location data and weighted reception location data)should be selected as refined location data for that particular firstcell. If the vehicle traverses the entire work area, a map or matrix ofvehicular cells versus selection of reception location data or opticallocation data (as refined location data) for the cells may be createdfor reference by the vehicle or another vehicle with substantiallysimilar sensor suite of a location-determining receiver 12 and anoptical location determining system 14. It should be noted that thereception quality module 20 may be removed for subsequent traversals ofthe vehicle over the work area, after the vehicle has prepared the mapor matrix of vehicular cells versus selection of reception location dataor optical location data. This may reduce the costs of hardware andweight for certain vehicular configurations.

The method of FIG. 3 is similar to the method of FIG. 2, except themethod of FIG. 3 deletes step S208 and adds steps S308, S310, and S312.Like reference numbers in FIG. 2 and FIG. 3 indicate like procedures orsteps.

In step S308, a location-sensing system 10 or dead-reckoning system 16determines dead-reckoning location data 30 within a first cell of a workarea for a vehicle.

In step S310, a quality estimation module 20 or a dead-reckoning qualityestimator 24 estimates dead-reckoning quality data 36 for thecorresponding dead-reckoning location data 30 for the first cell. Thework area may be divided into a group of cells or coordinate ranges,where each cell or coordinate range is associated with an availability,reliability, and or error of localization of the dead-reckoning system16 or the dead-reckoning location data 30. Where the work area isdivided into such cells or coordinate ranges, the odometer qualityestimator 24 may retrieve or access dead-reckoning quality data 36 for acorresponding first cell. The dead-reckoning quality data 36 mayconsider error accumulation rates, where the dead-reckoning locationdata 30 is not used to supplement, augment or in conjunction with thereception location data 26 and the optical location data 28. In oneexample, where the work area is a baseball stadium, the dead-reckoningquality data 36 may be obtained from empirical measurement and mayinclude different values for any of the following: dry grass, wet grass,dry artificial turf, wet artificial turf, outfield material, and infielddirt, infield sand or infield material. In another example, where thework area is a sports stadium, an arena, a soccer stadium, a footballstadium, golf course, the dead-reckoning quality data 36 may be obtainedfrom empirical measurement and may include different values for any ofthe following: dry grass, wet grass, dry artificial turf, wet artificialturf, golf rough, golf green, golf fairway, grass height, grassmoisture, grass variety, and ground moisture. In another example, thedead-reckoning quality data 36 may be obtained from empiricalmeasurements of a dry field, a wet field, a harvested field portion, anunharvested field portion, a plowed field portion, an unplowed fieldportion, a low-till portion, an exposed soil field, an unplanted fieldor the like.

In step S312, the data processor 38 selects at least one of thereception location data 26, the optical location data 28, and thedead-reckoning location data 30 as refined location data 40 associatedwith the first cell based on the estimated reception quality data 32,estimated optical quality data 34, and estimated dead-reckoning qualitydata 36. In one embodiment, the selecting process of step S312 iscarried out by the data processor 38, filter or switching matrixestablishing relative weights for application of the reception locationdata 26, the optical location data 28, and the dead-reckoning locationdata 30 based on the estimated reception quality data 32, estimatedoptical quality data 34, and estimated dead-reckoning quality data 36.For example, the relative weight of a location sensor is increased witha material increase in its corresponding quality and decreased with amaterial decrease in its corresponding quality. If the quality level ofany location sensor falls below a minimum threshold, the weight may bereduced to eliminate its contribution to the location solution orrefined location data 40.

During or after step S312, the data processor 38 may define first cellwith reference to the refined location data and store the first celllocation or boundaries in data storage 39 along with the correspondingselection of refined location data for subsequent reference.Accordingly, if the vehicle traverses the first cell again, the dataprocessor 38 may retrieve whether the optical location data, theodometer location data, and the reception location data (or weightedoptical location data, weighted odometer location data and weightedreception location data) should be selected as refined location data forthat particular first cell. If the vehicle traverses the entire workarea, a map or matrix of vehicular cells versus selection of receptionlocation data or optical location data (as refined location data) forthe cells may be created for reference by the vehicle or another vehiclewith substantially similar sensor suite of a location-determiningreceiver 12 and an optical location determining system 14. It should benoted that the reception quality module 20 may be removed for subsequenttraversals of the vehicle over the work area, after the vehicle hasprepared the map or matrix of vehicular cells versus selection ofreception location data or optical location data. This may reduce thecosts of hardware and weight for certain vehicular configurations.

FIG. 4 discloses a method for determining a location of a vehicle basedon site specific sensor quality data. The method of FIG. 4 begins instep S400.

In step S400, a quality estimation module 20 or user interface 18establishes an estimate of reception quality data 32 versus cellularlocations for work area and an estimate of optical quality data 34versus cellular location data. Under a first approach for executing stepS400, the quality estimation module 20 expresses the estimate as atleast one of a map, a contour map, a two-dimensional matrix, and amultidimensional matrix, a look-up table, a chart, and a database. Undera second approach for executing step S400, the quality estimation module20 expresses the estimate as a contour map having contours indicative ofa dilution-of-precision (DOP) value associated with at least one of thereception location data 26 and the optical location data 28. Thedilution of precision (DOP) value may comprise a Position Dilution ofPrecision, a Relative Dilution of Precision, a Horizontal Dilution ofPrecision, Vertical Dilution of Precision, Time Dilution of Precision,and Geometric Dilution of Precision.

In step S402, the location-sensing system 10 determines receptionlocation data 26 and optical location data 28 within a first cell of thecellular locations of a work area for a vehicle.

In step S404, the quality estimation module 20 references theestablished estimate to retrieve relevant reception quality data andrelevant optical quality data associated with the first cell.

In step S406, the data processor 38 selects at least one of thereception location data 26 and the optical location data 28 as refinedlocation data 40 associated with the first cell based on the relevantreception quality data 32 and the relevant optical quality data 24. Forexample, in the selection process of step S406, the data processor 38establishes relative weights for application of the reception locationdata 26 and the optical location data 28 based on the relevant receptionquality data 32 and relevant optical quality data 34, respectively.

The method of FIG. 5 is similar to the method of FIG. 4, except themethod of FIG. 5 further considers dead-reckoning location data 30 anddead-reckoning quality data 36. The method of FIG. 5 begins in stepS500.

In step S500, the quality estimation module 20 or the user interface 18establishes an estimate of reception quality data 32 versus cellularlocations for work area; an estimate of optical quality data 34 versuscellular locations for the work area; and an estimate of dead-reckoningquality data 36 versus cellular locations for the work area.

In step S502, the location-sensing system 10 determines receptionlocation data 26, optical location data 28, and dead-reckoning locationdata 30 within a first cell of the cellular locations of a work area fora vehicle.

In step S504, the quality estimation module 20 may reference theestablished estimate to retrieve relevant reception quality data 32,relevant optical quality data 34, and relevant dead-reckoning qualitydata 36 associated with the first cell.

In step S506, the data processor 38 selects at least one of thereception location data 26, the optical location data 28, anddead-reckoning location data 30 as refined location data 40 associatedwith the first cell based on the relevant reception quality data 32,relevant optical quality data 34, and the relevant dead-reckoningquality data 36. For example, in accordance with step S506, the dataprocessor 38 establishes relative weights for application of thereception location data 26, the optical location data 28, and thedead-reckoning location data 30 based on the relevant reception qualitydata 32, relevant optical quality data 34, and relevant dead-reckoningquality data 36.

FIG. 6 is a flow chart of a method for navigation of a vehicle. Themethod of FIG. 6 applies a hierarchical approach to the selection ofreception location data 26, optical location data 28, or dead-reckoninglocation data 30, as the refined location data 38. The method of FIG. 6begins in step S600.

In step S600, a quality estimation module 20 or a data processor 38determines whether a quality estimate (e.g., a site quality map) isavailable for a particular work area in which the vehicle plans tooperate or is operating. The vehicle has a vehicular position. If thequality estimate is available, then the method continues with step S611.However, if the quality estimate is not available, then the methodcontinues with step S602.

In step S611, the method of FIG. 6 applies the method of FIG. 2, FIG. 3,FIG. 4, or FIG. 5. For example, following step S611 the method maycontinue with step S200 of FIG. 2 or FIG. 3, step S400 of FIG. 4, orstep S500 of FIG. 5.

In step S602, a quality estimation module 20 or location-sensing system10 determines whether reception location data 26 is available or meets aDilution of Precision (DOP) threshold criteria for the correspondingvehicular position of the vehicle. If the reception location data 26 isavailable or meets the DOP threshold criteria, the method continues withstep S604. However, if the reception location data is not available orfails to meet the DOP threshold criteria, the method continues with stepS606. The reception location data may be considered unavailable wherethe displacement reported by the location determining receiver 12 isphysically “impossible” or inconsistent with reported displacements,considering the greater error of the available sources of reporteddisplacements for a given corresponding time.

In step S604, the data processor 38 applies available reception locationdata for vehicular navigation.

In step S606, a quality estimation module 20 or location-sensing system10 determines whether optical location data 28 is available, theestimated Dilution of Precision (DOP) meets a threshold DOP criteria, orthe figure of merit meets or exceeds a threshold for the correspondingvehicular position of the vehicle. If the optical location data 28 isavailable, meets a threshold DOP criteria, or the figure of merit meetsor exceeds a threshold, the method continues with step S607. However, ifthe optical location data 28 is not available, the method continues withstep S608.

In step S607, the data processor 38 applies available optical locationdata 28 for vehicular navigation. The optical location data may be usedto guide a vehicle with respect to visual landmarks (e.g., crop rows orplant rows in a field). An as-planted map where plants or portionsthereof (e.g., trunks) have known locations, may be used to guide thevehicle.

In step S608, a quality estimation module 20 or location-sensing system10 determines whether reception location data 26 is available or if thecumulative error (e.g., distance error integration estimate) is lessthan or equal to a maximum limit for the corresponding vehicularposition of the vehicle. If the reception location data 26 is availableor the cumulative error is less than or equal to the maximum limit, themethod continues with step S609. However, if the reception location isnot available or if the cumulative error (e.g., distance errorintegration estimate) is greater than the maximum limit, the methodcontinues with step S610.

In step S609, the data processor 38 applies available dead-reckoninglocation data 30 for vehicular navigation.

In step S610, the vehicle is stopped and it waits for a time interval tocontinue with step S602 or otherwise. During the wait, for example, oneor more satellite transmissions may improve the reception signal qualityof the location determining receiver, such that the reception locationdata 26 becomes available or meets a Dilution of Precision (DOP), forexample.

In an alternate example of step S610, a visual or audio alert system mayalert an operator that the vehicle has switched to manual guidance modeor an operator guided mode.

FIG. 7 is a map of error magnitude contours of one or more locationsensors or location sensing devices in a work area. Each contourrepresents a constant error level or a uniform error level range for oneor more of the following data measurements for location of the vehicle:reception location data 26, optical location data 28, and dead-reckoninglocation data 30. The first contour 806 is illustrated as a series oftwo adjacent dashes that interrupt a solid curved line. The secondcontour 808 is illustrated as alternating dots and dashes. The thirdcontour 810 is illustrated as a dashed line. The fourth contour 812 isillustrated as a dotted line. The fifth contour 814 is illustrated as asolid line. Although the first contour 806 is associated with a highestlevel of error here for illustrative purposes and the fifth contour 814is associated with a lowest level of error here, each contour may beassigned virtually any error level and fall within the scope of theinvention.

Although the units on the horizontal and vertical axes, are shown inmeters, any suitable measurement of spatial or distance dimensions maybe used in practice.

In one example, the reception location may have a first error magnitudecontour similar to that of FIG. 7; the optical location data 28 may havea second error magnitude contour that differs from that of FIG. 7, andthe dead-reckoning location data 30 may have a third error magnitudecontour that is independent or differs from those of the first errormagnitude contour and the second error magnitude contour. Although theerror magnitude contour is shown as contours (806, 808, 810, 812, and814) in FIG. 7, in an alternate embodiment the contours may berepresented by an illustrative chart, database, tabular data points,geometric equations, line equations, curve equations, or otherwise.

FIG. 8 is a map of navigation modes associated with particularcorresponding zones of the work area. The map of FIG. 8 is similar tothe map of FIG. 7 except in the map of FIG. 8: (1) the contours (806,808, 810,812 and 814) definitely represent error level or uniform errorrange for optical location data and (2) a group of zones (800, 802, and804) for corresponding navigational modes are shown. Each zone (800,802, or 804) represents an area where a different location sensor orcombination of sensors is preferred based on at least one of an errormagnitude contour for optical location data, odometer location data, andreception location data. For example, a first zone 800 may be associatedwith the location-determining receiver 12 and the reception locationdata 26 as the preferential location sensor and the preferentiallocation data, respectively. In the first zone 800, thelocation-determining receiver 12 provides acceptable error orreliability and the vision data does not.

A second zone 804 may be associated with an optical location-determiningsystem 14 and the optical location data 28 as the preferential locationsensing subsystem and the preferential location data, respectively. Inthe second zone 804, the optical location data 28 is acceptable and thereception location data 26 is not.

A third zone 802 may be associated with a dead-reckoning system 16 andthe dead-reckoning location data 30 as the preferential location sensingsubsystem and the preferential dead-reckoning location data 30,respectively. In a third zone 802, neither the reception location data26, nor the optical location data 28 provides acceptable error,availability or reliability.

Although the first zone 800 is generally elliptical; the third zone 802forms an elliptical and rectangular inner frame; the second zone 804forms a generally rectangular outer frame, other shapes of the zones arepossible and fall within the scope of the claimed invention. The vehiclemay use a map (e.g., the map of FIG. 8) or an equivalent datarepresentation thereof to switch between the reception location data 26,the optical location data 28, and the dead-reckoning location data 30for derivation of the refined location data 40 for guidance or pathplanning of the vehicle. Alternatively, the vehicle may use a map or anequivalent data representation thereof to apply different weights to thereception location data 26, the optical location data 28, and thedead-reckoning location data 30 for derivation of the refined locationdata 40. Accordingly, rather than using an on-off use of each sensor,the weighting may be accomplished by application of a Kalman filter toprovide a smoother sequence of calculated positions while avoidingdiscontinuities that might otherwise occur when shifting from one zoneto an adjacent zone.

FIG. 9 is another map of navigation modes associated with particularcorresponding zones of the work area. The map of FIG. 9 is similar tothe map of FIG. 8 except the map of FIG. 9 shows a path plan of thevehicle. Like reference numbers indicate like elements in FIG. 7, FIG. 8and FIG. 9.

The path plan of the vehicle is shown as several generally linearsegments (900, 901, 902, 903, 904, 905, 906, 907, and 908). The pathplan may be divided into a series of segments based on the intersectionof the path plan with various zones of preferential location data, theturns in the path plan, or both. At the intersection of the path planwith various zones, the intersections are shown as points for clarity.

Starting from a first path plan segment 900 on a right side of the mapof FIG. 9, the vehicle would be in a second zone 804 so that the opticallocation data 28 would be the preferential location data. In the secondpath segment 901, the vehicle would be in the third zone 802 such thatthe dead-reckoning location data 30 may be the preferential locationdata. This second path segment 901 may be susceptible to inaccuracy tocumulative error of the dead-reckoning system 16, unless appropriatepath diversions or reroutes are taken as described below. In the thirdpath segment 902 and fourth path segment 903, the vehicle would be inthe first zone 800 such that the reception location data 26 (e.g., GPSdata) would apply. In the fifth path segment 904, the vehicle would bein the third zone 802 such that the dead-reckoning location data 30 maybe the preferential location data. In the sixth path segment 905 and theseventh path segment 906, the vehicle would be in the second zone 804such that the optical location data 28 may be the preferential locationdata. In the eighth path segment 907, the vehicle would be in the thirdzone 802 such that the odometer location data 30 would apply. In theninth path segment 908, the vehicle would be in the first zone 800 suchthat the reception location data 26 would apply.

The path planning module 42 may alter the path plan (e.g., second pathsegment 901) to compensate for the errors that might otherwiseaccumulate in guidance or navigation of the vehicle. If the vehicle(e.g., a mower) uses strictly back-and forth motion vertically orhorizontally in generally parallel rows to cover a work area shown inFIG. 8, there will be several general areas where the vehicle may spendextensive amounts of time (e.g., in the third zone 802, depending on itsgeometric shape) where neither optical location data 28, nor receptionlocation data 26 is available to compensate for the cumulative error ofthe dead-reckoning location data 30. Accordingly, prior to thedead-reckoning quality data 36 exceeding a threshold cumulative error orexceeding a threshold maximum time in the third zone 802, the path planof the vehicle may be modified to enter into another zone (e.g., firstzone 800 or the second zone 804) where reception location data 26 oroptical location data 28 is available to truth or augment thedead-reckoning location data 30. Accordingly, path plans that changefrom one zone to another zone on a regular basis or prior to the elapseof a maximum time period may offer greater diversity of sensor type ofthe location-sensing system 10 and increased reliability.

For path planning purposes, the path planning module 42 may use thecalculated position error information, the reception quality data, theoptical quality data, or the dead-reckoning quality data 36 as acoverage overlap or adjacent row overlap allowance. If the calculatedmaximum error is approximately 10 centimeters, then the vehicle (e.g.,mower) could overlap the adjacent pass or row by approximately 10centimeters to ensure the vegetation is properly processed (e.g. mowed)or the treatment or crop input is properly disbursed. The maximum errorfor a pass could be used for the entire pass and then adjusted for themaximum error of the next path. If the optical location-determiningsystem 14 has pan, tilt or zoom rate limits, the pat planner cangenerate path plans that do not require the camera rate limits to beexceeded.

The method and system of vehicular navigation may be applied toresidential, golf course, and other mowers where Global PositioningSystem (GPS) signals may be blocked or attenuated by trees, buildings,or ground; timber harvesters and forwarders that occasionally orperiodically visit clearings (in a forested or wooded area), butotherwise work in areas where GPS signals are blocked by trees orterrain; farm machinery operating a field or farm yard where GPS signalsmay be blocked by buildings, trees or terrain; and construction andmilitary equipment where GPS signals may be blocked by trees, buildings,or terrain, and many other types of vehicles and equipment.

FIG. 10 is a flow chart of a method for determining a location of avehicle in accordance with predetermined zones in a work area. Thepredetermined zones may be established before the vehicle performs atask in the work area or traverses the work area to perform a function.The method of FIG. 10 begins with step S900.

In step S900, a first zone is established in a work area. For example, auser may define a first zone based on a survey or map (e.g., errormagnitude contour of FIG. 7) of reception quality data in the work areavia user interface 18 and quality estimation module 20. The first zoneis where reception location data is applied preferentially orexclusively as refined location data. In the first zone, the receptionlocation data is associated with a corresponding reception quality datathat meets or exceeds a certain minimum threshold of reliability withinthe first zone. Although the optical location data and the odometerlocation in the first zone may be unreliable or may vary too much to beuniformly reliable over the first zone, in one example the receptionlocation data may still be used for the first zone even where theoptical location data, the odometer location data, or both tend to bereliable within material areas of the first zone.

In one embodiment, the first zone may be defined by an outer perimeter,an inner perimeter or both. A series of points (e.g., two or threedimensional coordinates) may be defined on the outer perimeter and theinner perimeter, and stored in a storage device 39 associated with thedata processor 38.

In another embodiment, the first zone comprises a series of cells in thework area. It is possible that at least some of the cells of the firstzone are noncontinguous. The cells may have a uniform size and shape(e.g., polygonal). Each cell may be associated with its centralcoordinates, a range of coordinates, or its perimeter coordinates.

In step S902, a second zone is established in a work area. For example,a user may define a second zone based on a survey or map (e.g., errormagnitude contour of FIG. 7) of optical quality data in the work areavia user interface 18 and quality estimation module 20. The second zoneis where optical location data is applied preferentially or exclusivelyas refined location data. In the second zone, the optical location datais associated with a corresponding optical quality data that meets orexceeds a certain minimum threshold of reliability within the secondzone. Although the reception location data and the odometer location inthe second zone may be unreliable or may vary too much to be uniformlyreliable over the second zone, in one example the optical location datamay still be used for the second zone even where the reception locationdata, the odometer location data, or both tend to be reliable withinmaterial areas of the second zone.

In one embodiment, the second zone may be defined by an outer perimeter,an inner perimeter or both. A series of points (e.g., two or threedimensional coordinates) may be defined on the outer perimeter and theinner perimeter, and stored in a storage device 39 associated with thedata processor 38.

In another embodiment, the second zone comprises a series of cells inthe work area. It is possible that at least some of the cells of thesecond zone are noncontinguous. The cells may have a uniform size andshape (e.g., polygonal). Each cell may be associated with its centralcoordinates, a range of coordinates, or its perimeter coordinates.

In step S904, the location-determining receiver 12 determines thereception location data and the optical location-determining receiver 14determines optical location data to estimate preliminary location dataindicating whether the vehicle is located in the first zone or thesecond zone. It should be noted at this point in time in step S904, theexact position of the vehicle with absolute precision or certainty isnot known because there may be error associated with the receptionlocation data and optical location data. The preliminary location datamay be derived from the reception location data, the optical locationdata, or both.

The preliminary location data may be determined in accordance with thefollowing techniques, which may be applied individually or cumulatively.Under a first technique, the preliminary location data comprises thereception location data or the optical location data, if the receptionlocation data and the optical location data are coextensive or spacedapart by a maximum tolerance (e.g., a maximum specified distance).

Under a second technique, the preliminary location data comprises thegeometric mean or average of the reception location data and the opticallocation data, if the reception location data and the optical locationdata are coextensive or spaced apart by a maximum tolerance. Forinstance, a line segment interconnects the coordinates of the receptionlocation data and the optical location data, and the geometric mean oraverage is located on the line segment one-half of the distance betweenthe coordinates or ends of the line segment.

Under a third technique, the preliminary location data comprises theweighted geometric mean or weighted average of the reception locationdata and the optical location data, if the reception location data andthe optical location data are coextensive or spaced apart by a maximumtolerance. For instance, a line segment interconnects the coordinates ofthe reception location data and the optical location data, and theweighted geometric mean or weighted average is located on the linesegment on some distance (which is proportional to the weights assignedto the reception location data and optical location data) between thecoordinates or ends of the line segment.

Under a fourth technique, the preliminary location data comprises thereception location data, if the reception location data is available ormeets or exceeds a threshold level of reliability. Under a fifthtechnique, the preliminary location data comprises the optical locationdata, if the reception location data is not available or if thereception location data falls below a threshold level of reliability.

In step S906, a data processor 38 or selector selects at least one ofthe reception location data and the optical location as the refinedlocation data based on whether the preliminary location data fallswithin the established first zone or the second zone. The selectionprocess of step S906 may determine how to select the refined locationdata where the estimated preliminary data is inconclusive or suspect inreliability in accordance with various procedures, which may be appliedalternately or cumulatively. Under a first procedure, if the estimatedpreliminary location data is inconclusive with respect to whether thevehicle is located in the first zone, the second zone, the dataprocessor or selector selects the reception location data as the refinedlocation data. Under a second procedure if the estimated preliminarydata is inconclusive with respect to whether the vehicle is located inthe first zone or second zone and if the reception location data is notavailable, the data processor or selector selects the optical locationdata as the refined location data. Under a third procedure, if theestimated preliminary data is inconclusive with respect to whether thevehicle is located in the first zone or the second zone and if thereception location data falls below a threshold reliability level, thedata processor 38 or selector selects the optical location data as therefined location data. Under a fourth procedure, if the estimatedpreliminary data is inconclusive with respect to whether the vehicle islocated in the first zone or the second zone, the data processor 38 orselector may select or default to the last selected type of locationdata for the last verifiable zone in which the vehicle was present,unless more than a maximum threshold time has elapsed.

In considering practical implementation of the method of FIG. 10, thecumulative error of the vehicle relying on any one of the opticallocation data, the odometer location data, and the reception locationdata for an excessive time or over an excessive distance withoutcross-checking against diverse location data may lead to guidance errorsor drift. Accordingly, where the method of FIG. 10 is used to execute apath plan, one or more of the following limitations may be placed onover-reliance on any one of the location-determining receiver 12, theoptical location-determining system 14, and the dead-reckoning system16. Under a first illustrative limitation, a path planning module 42executes or determines a path plan of the vehicle such that the vehicleswitches between the first zone and the second zone within a certainmaximum time limit. Under a second illustrative limitation, a pathplanning module 42 executes or determines a path plan of the vehiclesuch that the vehicle switches between the first zone and the secondzone within a certain maximum distance traversed by the vehicle.

The method of FIG. 11 is similar to the method of FIG. 10, except themethod of FIG. 11 is expanded to include a third zone and odometerlocation data. Like reference numbers in FIG. 10 and FIG. 11 indicatelike steps or procedures.

After step S900 and step S902, the method continues with step S903. Instep S903, a third zone is established in a work area. For example, auser may define a third zone based on a survey or map (e.g., errormagnitude contour of FIG. 7) of optical quality data in the work areavia user interface 18 and the quality estimation module 20. The thirdzone is where odometer location data is applied preferentially orexclusively as refined location data. In the third zone, the odometerlocation data is associated with a corresponding dead-reckoning qualitydata 36 that meets or exceeds a certain minimum threshold of reliabilitywithin the third zone.

Although the reception location data and the optical location data inthe third zone may be unreliable or may vary too much to be uniformlyreliable over the third zone, in one example the odometer location datamay still be used for the third zone even where the reception locationdata, the optical location data, or both tend to be reliable withinmaterial areas of the third zone.

In one embodiment, the third zone may be defined by an outer perimeter,an inner perimeter or both. A series of points (e.g., two or threedimensional coordinates) may be defined on the outer perimeter and theinner perimeter, and stored in a storage device 39 associated with thedata processor 38.

In another embodiment, the third zone comprises a series of cells in thework area. It is possible that at least some of the cells of the thirdzone are noncontinguous. The cells may have a uniform size and shape(e.g., polygonal). Each cell may be associated with its centralcoordinates, a range of coordinates, or its perimeter coordinates.

In step S905, at least one of reception location data, optical locationdata, and odometer location data is determined to estimate preliminarylocation data. The preliminary location data indicates whether thevehicle is located in the first zone, the second zone or the third zone.

It should be noted at this point in time in step S905, the exactposition of the vehicle with absolute precision or certainty is notknown because there may be error associated with the reception locationdata, the optical location data, and the odometer location data. Thepreliminary location data may be derived from the reception locationdata, the optical location data, odometer location data, or anycombination of the foregoing location data.

The preliminary location data may be determined in accordance with thefollowing techniques, which may be applied individually or cumulatively.Under a first technique, the preliminary location data comprises thereception location data, the optical location data, or the odometerlocation data if the reception location data, the optical location data,and the odometer location data are coextensive or spaced apart by amaximum tolerance (e.g., a maximum specified distance) with respect toeach other.

Under a second technique, the preliminary location data comprises thegeometric mean or average of the closest two of the reception locationdata, the optical location data, and the odometer location data, if thereception location data, the optical location data, and the odometer arecoextensive or spaced apart with respect to each other by a maximumtolerance. For instance, a line segment interconnects the coordinates ofthe closest two of the reception location data, the optical locationdata, and the odometer location data; and the geometric mean or averageis located on the line segment one-half of the distance between thecoordinates or ends of the line segment extending between the closesttwo.

Under a third technique, the preliminary location data comprises theweighted geometric mean or weighted average of the reception locationdata, the optical location data, and the odometer location data if thereception location data, the optical location data, and the odometerlocation data are coextensive or spaced apart by a maximum tolerance.For instance, a line segment interconnects the coordinates of theclosest two of the reception location data, the optical location data,and the odometer location data, and the weighted geometric mean orweighted average is located on the line segment on some distance (whichis proportional to the weights assigned to the reception location dataand optical location data) between the coordinates or ends of the linesegment extending between the closest two.

Under a fourth technique, the preliminary location data comprises thereception location data, if the reception location data is available ormeets or exceeds a threshold level of reliability. Under a fifthtechnique, the preliminary location data comprises the optical locationdata, if the reception location data is not available or if thereception location data falls below a threshold level of reliability.

In step S909, the data processor 38 or selector selects at least one ofthe reception location data, the optical location data, and the odometerlocation data as the refined location data based on whether thepreliminary location data falls within the established first zone, theestablished second zone or the established third zone.

In considering practical implementation of the method of FIG. 11, thecumulative error of the vehicle relying on any one of the opticallocation data, the odometer location data, and the reception locationdata for an excessive time or over an excessive distance withoutcross-checking against diverse location data (other location dataavailable from the location sensing system 10) may lead to guidanceerrors or drift. Accordingly, where the method of FIG. 11 is used toexecute a path plan, one or more of the following limitations may beplaced on over-reliance on any one of the location-determining receiver12, the optical location-determining system 14, and the dead-reckoningsystem 16. Under a first illustrative limitation, a path planning module42 executes or determines a path plan of the vehicle such that thevehicle switches between the first zone and the second zone within acertain maximum time limit. Under a second illustrative limitation, apath planning module 42 executes or determines a path plan of thevehicle such that the vehicle switches between the first zone and thesecond zone within a certain maximum distance traversed by the vehicle.

Having described the preferred embodiment, it will become apparent thatvarious modifications can be made without departing from the scope ofthe invention as defined in the accompanying claims.

1. A method for determining a location of a vehicle, the methodcomprising: establishing an estimate of reception quality data versuscellular locations for a particular work area and an estimate of opticalquality data versus cellular location data to store the qualityestimates and reference them when the vehicle is in the particular workarea; determining reception location data and optical location datawithin a first cell of the cellular locations of the work area for avehicle; referencing the established quality estimates for theparticular work area to retrieve relevant stored reception quality dataand relevant stored optical quality data associated with the first cell;and selecting at least one of the reception location data and theoptical location data as refined location data associated with The firstcell based on the relevant stored reception quality data and relevantstored optical quality data.
 2. The method according to claim 1 whereinthe selecting comprises establishing relative weights for application ofthe reception location data and the optical location data based on therelevant stored reception quality data and relevant stored opticalquality data.
 3. The method according to claim 1 wherein theestablishing comprises expressing the quality estimates as at least oneof a map, a contour map, a two-dimensional matrix, and amultidimensional matrix, a look-up table, a chart, and a database. 4.The method according to claim 1 wherein the establishing comprisesexpressing the quality estimates as a contour map having contoursindicative of a dilution of precision value associated with at least oneof the reception location data and the optical location data.
 5. Themethod according to claim 1 wherein the selecting comprises: selectingthe reception location data as the refined location data associated withthe first cell; guiding the vehicle within the first cell based on theselected reception location data.
 6. The method according to claim 1wherein the selecting comprises: selecting the optical location data asthe refined location data associated with the first cell; guiding thevehicle within the first cell based on the selected optical locationdata.
 7. The method according to claim 1 Wherein the reception qualitydata comprises a dilution of precision that considers a number ofsatellites that are available with a reliable signal strength, a maximumbit error rate, or a maximum symbol error rate for a locationdetermining receiver at particular geographic coordinates.
 8. A methodfor determining a location Of a vehicle, the method comprising:establishing an estimate of reception quality data versus cellularlocations for a particular work area, an estimate of optical qualitydata versus cellular locations for the work area, and an estimate ofdead-reckoning quality data versus cellular locations for the particularwork area to store the quality estimates and reference them when thevehicle is in the particular work area; determining reception locationdata, optical location date, and dead-reckoning location data within afirst cell of the cellular locations of a the particular work area for avehicle; referencing the established quality estimates for theparticular work area to retrieve relevant stored reception quality data,relevant stored optical quality data, and relevant stored dead-reckoningquality data associated with the first cell; selecting at least one ofthe reception location data, the optical location data, anddead-reckoning location data as refined location data associated withthe first cell based on the relevant stored reception quality data,relevant stored optical quality data, and the relevant storeddead-reckoning quality data.
 9. The method according to claim 8 whereinthe establishing comprises expressing the quality estimates as at leastone of a map, a contour map, a two-dimensional matrix, and amultidimensional matrix, a look-up table, a chart, and a database. 10.The method according to claim 8 wherein the establishing comprisesexpressing the quality estimates as a contour map having contoursindicative of a dilution of precision value associated with at least oneof the reception location data, the optical location data, and thedead-reckoning location data.
 11. The method according to claim 8Wherein the selecting comprises establishing relative weights forapplication of the reception location data, the optical location data,and the dead-reckoning location data based of the relevant receptionquality data, relevant optical quality data, and relevant dead-reckoningquality data.
 12. The method according to claim 8 wherein the selectingcomprises: selecting the reception location data as the refined locationdata associated with the first cell; guiding the vehicle within thefirst cell based on the selected reception location data.
 13. The methodaccording to claim 8 wherein the selecting comprises: selecting theoptical location data as the refined location data associated with thefirst cell; guiding the vehicle within the first cell based on theselected optical location data.
 14. The method according to claim 8wherein the selecting comprises: selecting the dead-reckoning data asthe refined location data associated with the first cell; guiding thevehicle within the first cell based on the selected dead-reckoning data.15. The method according to claim 8 wherein the reception quality datacomprises a dilution of precision that considers a number of satellitesthat are available with a reliable signal strength, a maximum bit rate,or a maximum symbol error rate for a location determining receiver atparticular geographic coordinates.
 16. A system for determining alocation of a vehicle, the system comprising: a quality estimationmodule establishing an estimate of reception quality data versuscellular locations for a particular work area and an estimate of opticalquality data versus cellular location data to store the qualityestimates and referenced them when the vehicle is in the particular workarea; a location-determining receiver for determining reception locationdata within a first cell of the cellular locations of a the particularwork area for a vehicle; an optical location-determining receiver fordetermining optical location data within the first cell of the cellularlocations of the particular work area for the vehicle; a data processorfor referencing the established quality estimate for the particular workarea to retrieve relevant stored reception quality data and relevantstored optical quality data associated with the first cell; the dataprocessor selecting at least one of the reception location data and theoptical location data as refined location data associated with the firstcell based on the relevant stored reception quality data and relevantstored optical quality data.
 17. The system according to claim 16wherein the data processor selects relative weights for application ofthe reception location data and the optical location data based On therelevant stored reception quality data and relevant stored opticalquality data.
 18. The system according to claim 16 wherein theestablished quality estimates comprises at least one of a map, a contourmap, a two-dimensional matrix, and a multidimensional matrix, a look-uptable, a charts and a database.
 19. The system according to claim 16wherein the established quality estimates comprises a contour map havingcontours indicative of a dilution of precision value associated with atleast one of the reception location data and the optical location data.